SenseToKnow Autism Screening Device Validation Study

Autism Spectrum Disorder Clinical Trial

Official title:

SenseToKnow STAR Study: A Study of Technologies for Assessing Children's Development

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05874466
• Other study ID #: Pro00111371
• Secondary ID: 2P50HD093074
• Status: Recruiting
• Start date: July 7, 2023
• Est. completion date: August 2028

Study information

• Verified date: May 2024
• Source: Duke University
• Contact: Geraldine Dawson, PhD
• Phone: 9196680070
• Email: geraldine.dawson[@]duke.edu
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This is a pivotal, prospective, double-blind, study to evaluate the sensitivity and specificity of the SenseToKnow app for the detection of autism spectrum disorder in children 16-36 months of age.

Description:

This is a pivotal, prospective, double-blind, study to evaluate the sensitivity and specificity of the SenseToKnow app for the classification of autism spectrum disorder when administered by parents in a sample of patients 16-36 months of age. The trial design is a non-interventional cross-sectional study comparing the SenseToKnow app classification of autism spectrum disorder ("autism") versus non-autism with the patient's diagnostic status based on expert clinical diagnosis in a population of pediatric patients.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 350
• Est. completion date: August 2028
• Est. primary completion date: August 2028
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 16 Months to 36 Months

Eligibility

Inclusion Criteria:

1. Duke Health pediatric patient at enrollment

2. 16-<37 months of age at enrollment

3. Parent/legal guardian speaks English or Spanish

4. Parent/legal guardian understands and voluntarily provides informed consent

Exclusion Criteria:

1. Severe motor impairment that precludes study measure completion

2. Known genetic disorders

3. Severe hearing or visual impairment as determined on physical examination according to parent report

4. Acute illnesses likely to prevent successful or valid data collection

5. Uncontrolled epilepsy or seizure disorder

6. History or presence of a clinically significant medical disease, or a mental state that could confound the study or be detrimental to the subject as determined by the investigator

7. Acute exacerbations of chronic illnesses likely to prevent successful or valid data collection

8. Receiving therapies that affect vision

9. Parent/legal guardian and/or investigator believes that the child will be unable/unwilling to sit in the parent's lap to watch the app videos

10. Parent/legal guardian indicates that they or their child is unwilling or unable to complete the app administration, surveys, or diagnostic assessment

11. Participants who are otherwise judged as unable to comply with the protocol by the investigator

12. Any other factor that the investigator feels would make the study measures invalid

Related Conditions & MeSH terms

• Autism
• Autism Spectrum Disorder
• Autistic Disorder

Locations

Country	Name	City	State
United States	Duke University	Durham	North Carolina

Sponsors (2)

Lead Sponsor	Collaborator
Duke University	Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Sensitivity of SenseToKnow for autism detection	Sensitivity = #participants positive for autism on both SenseToKnow and expert clinical diagnosis / #participants positive for autism on both SenseToKnow and expert clinical diagnosis + #participants negative for autism on SenseToKnow who were positive for autism by expert clinical diagnosis	Will be calculated based on data from Baseline/Timepoint 1
Primary	Specificity of SenseToKnow for autism detection	Specificity = #participants negative for autism on both SenseToKnow and expert clinical diagnosis / #participants negative for autism on both SenseToKnow and expert clinical diagnosis + #participants positive for autism on SenseToKnow who were negative for autism by expert clinical diagnosis	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Positive Predictive Value of SenseToKnow (with and without adjustment for population prevalence)	The likelihood that a participant with a positive test result has a diagnosis of autism.	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Negative Predictive Value of SenseToKnow (with and without adjustment for population prevalence)	The likelihood that a participant with a negative test result does not have a diagnosis of autism	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC) with respect to the accuracy of the SenseToKnow app for autism versus non-autism classification	ROC is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. AUC measures the area underneath the entire ROC curve.	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Sensitivity of SenseToKnow + Parent Survey for autism detection	Sensitivity = #participants positive for autism on both SenseToKnow+Parent Survey and expert clinical diagnosis / # participants positive for autism on both SenseToKnow+Parent Survey and expert clinical diagnosis + #participants negative for autism on SenseToKnow+Parent Survey who were positive for autism by expert clinical diagnosis	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Specificity of SenseToKnow + Parent Survey Survey for autism detection	Specificity = #participants negative for autism on both SenseToKnow+Parent Survey and expert clinical diagnosis / #participants negative for autism on both SenseToKnow+Parent Survey and expert clinical diagnosis + #participants positive for autism on SenseToKnow+Parent Survey who were negative for autism by expert clinical diagnosis	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Positive Predictive Value of SenseToKnow + Parent Survey (with and without adjustment for population prevalence)	The likelihood that a participant with a positive test result has a diagnosis of autism.	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Negative Predictive Value of SenseToKnow + Parent Survey (with and without adjustment for population prevalence)	The likelihood that a participant with a negative test result does not have a diagnosis of autism	Will be calculated based on data from Baseline/Timepoint 1
Secondary	Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC) with respect to the accuracy of the SenseToKnow app + Parent Survey for autism versus non-autism classification	ROC is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. AUC measures the area underneath the entire ROC curve.	Will be calculated based on data from Baseline/Timepoint 1